Triple
T21096771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alabat Island |
E519786
|
entity |
| Predicate | hasLanguage |
P15
|
FINISHED |
| Object | Tagalog |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Tagalog | Statement: [Alabat Island, hasLanguage, Tagalog]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tagalog Context triple: [Alabat Island, hasLanguage, Tagalog]
-
A.
Tagalog
chosen
Tagalog is an Austronesian language primarily spoken in the Philippines and serves as the basis for the country’s national language, Filipino.
-
B.
Filipino
Filipinos are a Southeast Asian ethnolinguistic group native to the Philippines, known for their diverse Austronesian, Spanish, American, and Chinese cultural influences and a global diaspora.
-
C.
Ilocano
Ilocano refers to a major ethnolinguistic group from the northern Philippines, known for its distinct Ilocano language and rich agricultural and coastal cultural traditions.
-
D.
Kapampangan language
Kapampangan is an Austronesian language of the Philippines primarily spoken in the Pampanga region of Central Luzon.
-
E.
Binisaya
Binisaya is a major Austronesian language of the Philippines, widely spoken in the Central Visayas and parts of Mindanao.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e0b508d8dc81909be940dafe36c8f7 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e71b595cdc8190ba7a6f3f71d40c3f |
completed | April 21, 2026, 6:38 a.m. |
Created at: April 16, 2026, 2:52 p.m.